System and Method Providing Levelness of a Production Schedule

ABSTRACT

A system and method are disclosed for providing levelness of a production schedule. The system includes a computer configured to access demand data of one or more items to be processed within a sequence of tasks, access the demand data of the one or more items, calculate one or more time intervals for each of the one or more items, and calculate a weighted average for each of the one or more items. The computer is further configured to calculate a time ratio according to the sequence of tasks by calculating the average of the calculated time intervals and the calculated weighted averages and calculating a minimum ratio of an adjusted time interval for each of the one or more items and the calculated weighted averages. The computer is still further configured to generate a production schedule based on a sequence of tasks having a predetermined calculated time ratio.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/774,202, filed May 5, 2010, entitled “System and Method ProvidingLevelness of a Production Schedule,” which claims the benefit under 35U.S.C. §119(e) of U.S. Provisional Application Ser. No. 61/175,989,filed 6 May 2009, entitled “System and Method for Providing Levelness.”U.S. patent application Ser. No. 12/774,202 and Provisional ApplicationNo. 61/175,989 are commonly assigned to the assignee of the presentapplication. The subject matter disclosed in U.S. ProvisionalApplication No. 61/175,989 and U.S. patent application Ser. No.12/774,202 is hereby incorporated by reference into the presentdisclosure as if fully set forth herein.

TECHNICAL FIELD

The present disclosure relates generally to production scheduling moreparticularly to a system and method for providing levelness of aproduction schedule.

BACKGROUND

In lean manufacturing environments, one of the objectives is to spreadout all tasks in a schedule to produce a type of level pattern thatstabilizes the requirements on upstream suppliers and processes.However, in traditional lean manufacturing environments, there iscurrently no mechanism to measure the quality of the levelness of theproduction schedule. The inability to measure the levelness of aproduction schedule is undesirable.

SUMMARY

A system providing levelness of a production schedule is disclosed. Thesystem includes a database that stores demand data of one or more itemsto be processed within a sequence of tasks. The system further includesa computer coupled with the database and configured to access demanddata of one or more items to be processed within a sequence of tasks,access the demand data of the one or more items, calculate one or moretime intervals for each of the one or more items, and calculate aweighted average for each of the one or more items. The computer isfurther configured to calculate a time ratio according to the sequenceof tasks by calculating the average of the calculated time intervals andthe calculated weighted averages and calculating a minimum ratio of anadjusted time interval for each of the one or more items and thecalculated weighted averages. The computer is still further configuredto generate a production schedule that has a high degree of levelnessfor the given product mix and store the generated production schedule inthe database

A method of providing levelness of a production schedule is alsodisclosed. The method provides for accessing demand data of one or moreitems to be processed within a sequence of tasks, calculating one ormore time intervals for each of the one or more items, and calculating aweighted average for each of the one or more items. The method furtherprovides for calculating a time ratio according to the sequence of tasksby calculating the average of the calculated time intervals and thecalculated weighted averages and calculating a minimum ratio of anadjusted time interval for each of the one or more items and thecalculated weighted averages. The method still further provides forgenerating a production schedule that has a high degree of levelness forthe given product mix and storing the generated production schedule inthe database.

A computer-readable medium embodied with software providing levelness ofa production schedule is also disclosed. The software when executedusing one or more computers is configured to access demand data of oneor more items to be processed within a sequence of tasks, calculate oneor more time intervals for each of the one or more items, and calculatea weighted average for each of the one or more items. The software isfurther configured to calculate a time ratio according to the sequenceof tasks by calculating the average of the calculated time intervals andthe calculated weighted averages and calculating a minimum ratio of anadjusted time interval for each of the one or more items and thecalculated weighted averages. The software is still further configuredto generate a production schedule that has a high degree of levelnessfor the given product mix and store the generated production schedule inthe database

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features believed characteristic of the invention are setforth in the appended claims. However, the invention itself, as well asa preferred mode of use, and further objectives and advantages thereof,will best be understood by reference to the following detaileddescription when read in conjunction with the accompanying drawings,wherein:

FIG. 1 illustrates an exemplary system according to a preferredembodiment;

FIG. 2 illustrates an exemplary sequence of tasks in accordance with thepreferred embodiment; and

FIG. 3 illustrates an exemplary method of generating a productionschedule in the exemplary system.

DETAILED DESCRIPTION

Reference will now be made to the following detailed description of thepreferred and alternate embodiments. Those skilled in the art willrecognize that the present invention provides many inventive conceptsand novel features, that are merely illustrative, and are not to beconstrued as restrictive. Accordingly, the specific embodimentsdiscussed herein are given by way of example and do not limit the scopeof the present invention.

FIG. 1 illustrates an exemplary system 100 according to a preferredembodiment. System 100 comprises one or more planners 110, one or moreentities 120 a-120 n, a network 130, and communication links 132 and 134a-134 n. Although one or more planners 110, one or more entities 120a-120 n, and a single network 130, are shown and described; embodimentscontemplate any number of planners 110, any number of entities 120 a-120n, and/or any number of networks 130, according to particular needs. Inaddition, or as an alternative, one or more planners 110 may be integralto or separate from the hardware and/or software of any one of the oneor more entities 120 a-120 n.

In one embodiment, one or more entities 120 a-120 n represent a supplychain network including one or more supply chain entities, such as, forexample suppliers, manufacturers, distribution centers, retailers,and/or customers. A supplier may be any suitable entity that offers tosell or otherwise provides one or more parts (i.e., materials,components, or goods) to one or more other supply chain entities. Amanufacturer may be any suitable entity that manufactures at least oneitem. A manufacturer may use one or more parts, from one or moreupstream suppliers, during the manufacturing process to produce one ormore items. A manufacturer may generate a production schedule (i.e., aset of ordered tasks) in order to produce the one or more items. Asequence of tasks is a contiguous set of tasks that repeats throughout aproduction schedule at a manufacturer in producing the one or moreitems.

In addition, or as an alternative, a subsequence of tasks is acontiguous set of tasks that starts with a particular item and onlycontains one element of that item. That is, the subsequence is acontiguous set of tasks within a sequence of tasks that starts with aparticular item and contains only one task of that particular item andis followed by that particular item in the next subsequence, ifapplicable. In addition, the subsequence may go beyond the end of thesequence of tasks by assuming that the sequence repeats.

A manufacturer may, for example, produce and sell items to a supplier,another manufacturer, a distribution center, a retailer, a customer, orany other suitable person or entity. A distribution center may be anysuitable entity that offers to sell or otherwise distributes at leastone item to one or more retailers and/or customers. A retailer may beany suitable entity that obtains one or more items to sell to one ormore customers.

Although one or more entities 120 a-120 n is shown and described asseparate and distinct entities, the same person or entity cansimultaneously act as any one of the one or more entities 120 a-120 n.For example, one or more entities 120 a-120 n acting as a manufacturercould produce an item, and the same entity could act as a supplier tosupply an item to another supply chain entity. Although one example of asupply chain network is shown and described, embodiments contemplate anyoperational environment and/or supply chain network, without departingfrom the scope of the present invention.

In one embodiment, one or more planners 110 comprise one or morecomputers 112, one or more servers 114, and one or more databases 118.In addition, or as an alternative, one or more planners 110 and/or oneor more entities 120 a-120 n may each operate on one or more computersystems including one or more computers 112 that are integral to orseparate from the hardware and/or software that support system 100.These one or more computer systems may include any suitable inputdevice, such as a keypad, mouse, touch screen, microphone, or otherdevice to input information. These one or more computer systems may alsoinclude any suitable output device to convey information associated withthe operation of one or more planners 110 and one or more entities 120a-120 n, including digital or analog data, visual information, or audioinformation. These one or more computer systems may include fixed orremovable computer storage media, such as magnetic computer disks,CD-ROM, or other suitable computer-readable storage media to receiveoutput from and provide input to system 100. These one or more computersystems may include one or more processors and associated memory toexecute instructions and manipulate information according to theoperation of system 100. Each of these one or more computer systems maybe a work station, personal computer (PC), network computer, notebookcomputer, personal digital assistant (PDA), cell phone, wireless device,telephone, wireless data port, or any other suitable computing device.

In one embodiment, the memory associated with these one or more computersystems comprises any of a variety of data structures, arrangements,and/or compilations configured to store and facilitate retrieval ofinformation. The memory may, for example, comprise one or more volatileor non-volatile memory devices. Although the memory is described asresiding within these one or more computer systems, the memory mayreside in any location or locations that are accessible by one or morecomputers 112 or the one or more processors. The memory receives andstores information related to the levelness of one or more productionschedules involving multiple items associated with, for example, one ormore entities 120 a-120 n. The one or more processors processesinformation stored in the memory and accesses data representing thedemand of items to be processed within an ordered set of tasks andprovides the levelness of and generating of production schedules for thesequence of tasks associated with one or more entities 120 a-120 n. Thememory stores and the one or more processors process any suitableinformation to perform one or more production scheduling operationsassociated with one or more entities 120 a-120 n.

In an embodiment, one or more servers 110 comprise one or more sequenceengines 116. Although one or more servers 114 is shown and described ascomprising one or more sequence engines 116, embodiments contemplate anysuitable engines, solvers, or combination of engines and/or solvers,according to particular needs. One or more databases 118 comprises oneor more databases or other data storage arrangements at one or morelocations, local to, or remote from, one or more servers 114. One ormore databases 220 may be coupled with one or more servers 114 using oneor more local area networks (LANs), metropolitan area networks (MANs),wide area networks (WANs), network 130, such as, for example, theInternet, or any other appropriate wire line, wireless, or other links.

One or more databases 118 stores data to be used by one or more servers114. One or more databases 118 may include data representing the demandof items to be processed within an ordered set of tasks, levelness of aproduction schedule, and one or more rules associated with one or moreentities 120 a-120 n. In one embodiment, the data representing thelevelness of a production schedule may be used by one or more sequenceengines 116 to measure and optimize the levelness of a productionschedule associated with one or more entities 120 a-120 n. In addition,or as an alternative, one or more sequence engines 116 uses the datarepresenting the levelness as an objective function of a sequence oftasks, for example, in order to maximize profit, minimize cost, or thelike. In another embodiment, these one or more rules may be used by oneor more sequence engines 116 to minimize constraints, business rules,and penalties associated with one or more entities 120 a-120 n.

In an embodiment, one or more users are associated with one or moreplanners 110 and/or one or more entities 120 a-120 n. These one or moreusers include, for example, a “production planner” handling managementand planning of the sequences of tasks, levelness of the productionschedules and/or one or more related operations within system 100. Inone embodiment, these one or more related operations include accessingdata representing the demand of items to be processed, measuring thelevelness of and generating production schedules for the sequence oftasks. In addition, or as an alternative, these one or more productionplanners within system 100 includes, for example, one or more computersystems programmed to autonomously handle planning and/or one or morerelated operations within system 100. As discussed above, one or moreservers 114 may support one or more sequence engines 116, including oneor more planning engines, which store, retrieve, measure, and generateproduction schedules based on inputs received from one or more entities120 a-120 n, one or more production planners and/or one or moredatabases 118, as described more fully herein.

In one embodiment, one or more planners 110 is coupled with network 130using communications link 132, which may be any wireline, wireless, orother link suitable to support data communications between one or moreplanners 110 and network 130 during operation of system 100. One or moreentities 120 a-120 n are coupled with network 130 using communicationslinks 134 a-134 n, which may be any wireline, wireless, or other linksuitable to support data communications between one or more entities 120a-120 n and network 130 during operation of system 100. Althoughcommunication links 132 and 134 a-134 n are shown as generally couplingone or more planners 110 and one or more entities 120 a-120 n to network130, one or more planners 110 and one or more entities 120 a-120 n maycommunicate directly with each other, according to particular needs.

In addition, or as an alternative, network 130 includes the Internet andany appropriate local area networks (LANs), metropolitan area networks(MANS), or wide area networks (WANs) coupling one or more planners 110and one or more entities 120 a-120 n. For example, data may bemaintained by one or more planners 110 at one or more locations externalto one or more planners 110 and one or more entities 120 a-120 n andmade available to one or more associated users of one or more entities120 a-120 n using network 130 or in any other appropriate manner. Thoseskilled in the art will recognize that the complete structure andoperation of communication network 130 and other components withinsystem 100 are not depicted or described. Embodiments may be employed inconjunction with known communications networks and other components.

FIG. 2 illustrates an exemplary production schedule 200 in accordancewith the preferred embodiment. As discussed above, a production scheduleat one or more entities 120 a-120 n includes a sequence of tasks thatrepresents a contiguous set of tasks that repeats throughout theproduction schedule in producing items. In addition, a task is aninstance of producing an item at one or more entities 120 a-120 n. Inthis exemplary embodiment, sequence of tasks 210 a-210 n represents acontiguous set of tasks that repeats throughout production schedule 200in producing items A, B, and C. As an example only, and not by way oflimitation, sequence of tasks 210 a represents a total demand of tentasks at one or more entities 120 a-120 n, which is repeated throughoutproduction schedule 200 for producing items A, B, and C. Morespecifically, sequence of tasks 210 a represents a demand of five tasksfor producing item A, three tasks for producing item B and two tasks forproducing item C. Although an exemplary sequence of tasks 210 a is shownand described comprising particular items and a particular demandassociated with each item, embodiments contemplate any suitable numberof items, any suitable demand, or any combination of items and/ordemand, according to particular needs.

In one embodiment, one or more planners 110 optimizes productionschedule 200 to a state of levelness by, for example, spreading out thetasks in sequence of tasks 210 a, such that, the duration of the maximuminterval between two production runs of the same item decreases. Thatis, one or more planners 110 optimizes the levelness of sequence oftasks 210 a, by calculating a Takt time ratio TTR, discussed in moredetail below, and adjusting the order of the tasks in sequence of tasks210 a by spreading the tasks associated with each item until a levelsequence of tasks is achieved.

In addition, the Takt time ratio TTR provides one or more planners 110with a consistent levelness indicator (i.e., fixed indicator between 0and 10). For example, an indicator between 0 and 9 generally indicates acorrectable unlevelness, an indicator between 9 and 10 generallyindicates a possible mix of tasks conflict constraining levelness, andan indicator equal to 10 essentially indicates perfect levelness. In oneembodiment, perfect levelness is achievable whenever the mix of tasksdoes not constrain and/or hinder the levelness of any item, such as, forexample, when only two item types are mixed, or when the mix of tasks isevenly proportioned among any number of item types. In addition,embodiments provide compensation for simple sequences in which a maximumsequence is less than 9 and/or certain unlevel sequences which yield aTakt time ratio TTR greater than 9, such as by using one or more rulesstored in database 118.

In one embodiment, one or more planners 110 determines the levelness ofsequence of tasks 210 a by calculating a Takt Time Ratio (TTR) usingEquation (1):

TTR=TTR₁+[TTR₂]  (1)

TTR₁=Average of T_(A)/M_(A) for all items A

-   -   T_(A)=D/D_(A) Takt Time Interval        -   D=Demand: number of tasks in sequence        -   D_(A)=Demand of type A: number of type A tasks in sequence    -   M_(A)=Weighted Average of the number of tasks in A subsequences        having ≧[T_(A)] tasks.        -   Note number of tasks in each A subsequence having X≧[T_(A)]            tasks        -   Count each sequence duration 1+[|T_(A)−X|] times.    -   TTR₂=Min(1, T′_(A)/M_(A)) for all items A        -   T′_(A)=[T_(A)+1] Adjusted Takt Time Interval

As shown in equation (1), the [X] (square bracket) is an integerfunction which is the largest whole number smaller than or equal to thenumber in the brackets (i.e., [X]=greatest integer≦X).

In an embodiment, the Takt Time Ratio TTR₁ is an average of a ratio typeof all the items in sequence of tasks 210 a, that is, in this exemplaryproduction schedule 200, items A, B, and C. In addition, Takt Time RatioTTR₁ includes a numerator of a Takt time interval T_(i) and adenominator of a weighted average M_(i) of the number of tasks in itemtype i subsequences having ≧T_(i) tasks, where i varies over all theitem types of A-N. In addition, or as an alternative, Takt time intervalT_(i) is a ratio where numerator D is the total number of tasks insequence of tasks 210 a and denominator D_(i) is the number of tasks ofa particular item type (i.e., item types A, B, and C).

In one embodiment, the Takt time interval T_(i) is an objective (i.e., agoal of the one or more rules for the size of the subsequence). Forexample, in a perfectly level sequence of tasks, each subsequence ofitem type A should be of a duration T_(A), each subsequence of item typeB should be of a duration T_(B), each subsequence of type C should be ofa duration T_(C), and so on. In addition, or as an alternative, weightedaverage M_(A) is a weighted average of the number tasks in item type Asubsequences that have more than T_(A) tasks. If the number of tasks ineach subsequence has more T_(A) tasks in it, then one or more planners110 counts that sequence that many times in the weighted average M_(A).In essence, this provides one or more planners 110 a mechanism ofmeasuring the larger subsequences in an unleveled schedule.

In addition, or as an alternative, Takt Time Ratio TTR₂ is the smallestof a number of terms for each item i, or for all items A-N, upperbounded by unity. This is the same ratio as in the Takt Time Ratio TTR₁,except that the ratio includes an adjusted Takt time interval T′_(A)which provides an adjustment in the calculation. As illustrated inequation (1) the Takt Time Ratio TTR₂ is multiplied by 9, which providesthe bulk of the score and Takt Time Ratio TTR₁ provides a fine tuningmeasure, which is added to Takt Time Ratio TTR₂.

To further explain the operation of optimizing the sequence of tasks inproduction schedule 200 to a state of levelness, an example is nowgiven. In the following example, and as discussed above, sequence oftasks 210 a represents a total demand D of 10 tasks that is a totaldemand D_(A) of 5 tasks to produce item A, a total demand D_(B) of 3tasks to produce item B, and a total demand D_(C) of 2 tasks to produceitem C. Although a particular sequence of tasks 210 a is shown anddescribed, embodiments contemplate any suitable sequence of tasks,without departing from the scope or principles of the present invention.Based on equation (1), one or more planners 110 determines the Takt timeinterval T_(A) for each of items A, B, and C to be T_(A)=2, T_(B)=3.33,and T_(C)=5. Therefore, in a perfectly level sequence of tasks 210 a,item A would need to be produced every 2 tasks, item B would need to beproduced every 4 tasks, and item C would need to be produced every 5tasks. Put another way, in any set of 2 tasks in sequence of tasks 210a, there needs to be an item type A in order to get all item A'sproduced in, and spread out properly in a perfectly level sequence oftasks.

Continuing with this example and based on the order of tasks in sequenceof tasks 210 a one or more planners 110 determines the number ofsubsequences composed of [X] tasks where X≧[T_(A)] and calculates theweighted average M_(i) for each of items A, B, and C in sequence oftasks 210 a. That is, as shown in the first sequence of tasks ofsequence of tasks 210 a there is only one item A subsequence with atleast 2 tasks which includes a subsequence of 6 tasks, denoted as 6A's.Therefore, the weight on item A subsequence of 6 tasks is 5(1+[|T_(A)−X|] or 1+[|2−6|]) and the weighted average M_(A) for item Ais 6 ((5×6)/(5×1)). In addition, as shown in the first sequence of tasksof sequence of tasks 210 a there is only one item B subsequence with atleast [3.33]=3 tasks which includes a subsequence of 8 tasks, denoted as8B's. Therefore, the weight on item B subsequence of 8 tasks is 6(1+[|T_(B)−X|] or 1+[|3−8|]) and the weighted average M_(B) for item Bis 8 ((6×8)/(6×1)). Furthermore, as shown in the first sequence of tasksof sequence of tasks 210 a there is only one item C subsequence with atleast 5 tasks which includes a subsequence of 9 tasks, denoted as 9C's.Therefore, the weight on item C subsequence is 5 (1+[|T_(C)−X|] or1+[|5−9|]) and the weighted average M_(C) for item C is 9 ((5×9)/(5×1)).

Next, one or more planners calculate the Takt time ratio TTR₁ which, asshown in Equation (1) is the average of the Takt time interval T_(A) andthe weighted average M_(A). Based on the above calculated Takt timeinterval T_(A) and the weighted average M_(A) for items A, B, and C, theTakt time ratio TTR₁ of the first sequence of tasks of sequence of tasks210 a is 0.44, which is the average of {2/6, 3.33/8, 5/9}. Next one ormore planners 110 calculates the adjusted Takt time ratio TTR₂ ofsequence of tasks 210 a as 0.5, which is the Min(1, [T_(i)+1]/M_(i))over all i in {A, B, C} which is the minimum of {1, 3/6, 4/8, 6/9}. Oneor more planners 110 then calculates the Takt time ratio TTR of thefirst sequence of tasks of sequence of tasks 210 a as 4.44, which, asshown in Equation (1) is TTR₁+[9×TTR₂] (0.44+[9×0.5]=4.44).

As discussed below in more detail, one or more planners 110 optimizesproduction schedule 200 to a state of levelness by, for example,adjusting the order of the tasks by spreading the tasks associated witheach item, until a level sequence of tasks is achieved. In addition,each time a new sequence of tasks is adjusted one or more planners 110calculates the Takt time ratio TTR of sequence of tasks 210 a andadjusts the order of the tasks until a level sequence of tasks isachieved.

Continuing with this example, and with reference to the Nth sequence oftasks of sequence of tasks 210 a the Takt time interval T_(A) remainsthe same as determined above, however, the weighted averages M_(i)changes because the tasks are spread out into additional subsequences.In one embodiment, one or more planners 110 determine the number ofsubsequences with at least X tasks and calculates the weighted averageM_(i) for each of items A, B, and C in the Nth sequence of tasks ofsequence of tasks 210 a. That is, as shown in the Nth sequence of tasksof sequence of tasks 210 a there are now four item A subsequences withat least 2 tasks which includes three subsequences of 2 tasks and onesubsequence of 3 tasks, denoted as 2A's and 3A's. Therefore, since thereis more than one subsequence with different numbers of tasks in eachsubsequence, the weighted averages are calculated for each subsequenceincluding the different number of tasks. The weight on item Asubsequence of 2 tasks is 1 (1+[|T_(A)−X|] or 1+[|2−2|]) and the weighton item A subsequence of 3 tasks is 2 (1+[|T_(A)−X|] or 1+[|2−3|]). Theweighted average M_(A) for item A is 2.44, the average of {2, 2, 2, 3,3}.

In addition, as shown in the Nth sequence of tasks of sequence of tasks210 a there are now two item B subsequences with at least [3.33]=3 taskswhich includes two subsequences of 4 tasks, (note that there is onesubsequence with 2 tasks, however, this is not used in the calculation,since 2 tasks is not greater than or equal to 3 tasks). Therefore, theweight on item B subsequence of 4 tasks is 1 (1+[|T_(B)−X|] or1+[|3.33−4|] or 1+[|−0.67|]=1+0=1) and the weighted average M_(B) foritem B is 4, the average of {4, 4}. Furthermore, as shown in the Nthsequence of tasks of sequence of tasks 210 a there are now twosubsequences with at least 5 tasks which includes two subsequences of 5tasks. Therefore, the weight on item C subsequence of 5 tasks is 1(1+[|T_(C)−X|] or 1+[|5−5|]) and the weighted average M_(C) for item Cis 5, the average of {5, 5}.

Next, one or more planners calculates Takt time ratio TTR₁ based on theabove calculated Takt time interval T_(A) and the weighted average M_(A)for items A, B, and C, the Takt time ratio TTR₁ of the Nth sequence oftasks of sequence of tasks 210 a is 0.89, which is the average of{2/2.4, 3.33/4, 5/5}. Next one or more planners 110 calculates theadjusted Takt time ratio TTR₂ as 1, which is the Min(1, [T_(i)+1]/M)over all i in {A, B, C}, which is the minimum of {1, 3/2.4, 4/4, 6/5}.One or more planners 110 then calculates the Takt time ratio TTR of theNth sequence of tasks of sequence of tasks 210 a as 9.89, which, asshown in Equation (1) is TTR₁+[9×TTR₂].

As shown above, embodiments provide for optimizing production schedule200 to a state of levelness, that is embodiments provide for spreadingout the tasks in the first sequence of tasks of sequence of tasks 210 aand adjusting the order of the tasks by spreading the tasks associatedwith each item, until a Nth sequence of tasks of sequence of tasks 210 ais achieved with acceptable levelness (i.e., the sequence having apredetermined Takt time ratio TTR, such as, for example, the highestcalculated Takt time ratio TTR).

FIG. 3 illustrates an exemplary method 300 of generating a productionschedule in system 100. One or more planners 110 begins the method atstep 302 by accessing a sequence of tasks and the total demand of allitems to be processed in the sequence of tasks from one or more entities120 a-120 n. At step 304, one or more planners 110 accesses the demandof a particular item to be processed in the sequence of tasks from theone or more entities 120 a-120 n. As discussed above, the demand of theparticular item is represented as the number of particular item tasks inthe sequence of tasks. In addition, as discussed in more detail below,steps 304-308 are repeated for each additional item to be processed inthe sequence of tasks.

At step 306, one or more planners 110 calculates the Takt time intervalT_(A) of the particular item to be processed in the sequence of tasksbased on the total demand (i.e., the total number of tasks in thesequence of tasks accessed in step 302) and the demand for theparticular item (i.e. the total number of tasks for the particular itemin the sequence of tasks accessed in step 304). At step 308, one or moreplanners 110 determines the number of subsequences with X≧[T_(i)] tasksand calculates the particular items weighted average Mi of the number oftasks in the particular items subsequences having ≧[T_(i)] tasks. One ormore planners 110 calculates for each subsequence, the weight on eachsubsequence of X tasks=1+[|T_(A)−X|]. That is, the weight of eachsubsequence of tasks determines how many times the number of tasks inthe subsequence is used in the calculation of the weighted averageM_(i). One or more planners 110 then calculates the weighted average ofthe subsequence(s) of tasks. As an example only, and not by way oflimitation, if the weight is 1 then one or more planners 110 counts thenumber of tasks in the subsequence once in the calculation of theweighted average M_(i), if the weight is 2, then one or more planners110 counts the number of tasks in the subsequence twice in thecalculation of the weighted average M_(i), and so on.

At step 310, one or more planners 110 determines whether there isanother item to be processed in the sequence of tasks based on thesequence of tasks accessed in step 302. If there is another item, themethod returns to step 304 to access the demand of the additional item,calculate the Takt time interval T_(A) of the additional item to beprocessed, and calculate the additional item's weighted average Mi ofthe number of tasks in the additional items subsequences, otherwise, themethod proceeds to step 312.

At step 312, one or more planners 110 calculates the Takt time ratioTTR₁ which is the average of the ratios of the Takt time interval andthe weighted average (Ti/Mi). At step 314, one or more planners 110calculates the Takt time ratio TTR₂ which is the adjusted Takt timeinterval (i.e., TTR₂=Min(1,T′_(i)/M_(i)) for all items i). At step 316,one or more planners 110 calculates the Takt time ratio based on thecalculated Takt time ratio TTR₁ and the adjusted Takt time ratio TTR₂and stores the Takt time ratio TTR in database 118.

At step 318, one or more planners 110 compares the calculated Takt timeratio TTR from step 316 with previous stored Takt time ratio TTR indatabase 118 and determines if additional optimization is required. Ifadditional optimization is required, the method proceeds to step 320,otherwise, the method proceeds to step 322. At step 320, one or moreplanners 110 adjusts the order of the tasks by spreading the tasksassociated with each item in the sequence of tasks, thereby creating anew sequence of tasks. The method then returns to step 302 to repeat forthe new sequence of tasks steps 302-318.

At step 322, one or more planners 110 generates a production schedulebased on a sequence of tasks having a predetermined calculated Takt timeratio TTR, such as, for example, a highest calculated Takt time ratioTTR and stores the generated production schedule in database 118. Atstep 324, one or more planners 110 communicates the generated productionschedule to one or more entities 120 a-120 n and the method ends. Inaddition, although, FIG. 3 illustrates one embodiment of a method ofgenerating a production schedule in system 100, various changes may bemade to method 300 without departing from the scope of embodiments ofthe present invention.

Reference in the foregoing specification to “one embodiment”, “anembodiment”, or “another embodiment” means that a particular feature,structure, or characteristic described in connection with the embodimentis included in at least one embodiment of the invention. The appearancesof the phrase “in one embodiment” in various places in the specificationare not necessarily all referring to the same embodiment.

While the exemplary embodiments have been shown and described, it willbe understood that various changes and modifications to the foregoingembodiments may become apparent to those skilled in the art withoutdeparting from the spirit and scope of the present invention.

What is claimed is:
 1. A system providing levelness of a productionschedule, comprising: a database that stores demand data of one or moreitems to be processed within a sequence of tasks; and a computer coupledwith the database and configured to: access the demand data of the oneor more items; calculate one or more time intervals for each of the oneor more items; calculate a weighted average for each of the one or moreitems; calculate a time ratio according to the sequence of tasks by:calculating the average of the calculated time intervals and thecalculated weighted averages; and calculating a minimum ratio of anadjusted time interval for each of the one or more items and thecalculated weighted averages, upper bounded by unity; generate aproduction schedule based on a sequence of tasks having a predeterminedcalculated time ratio; and store the generated production schedule inthe database.
 2. The system of claim 1, wherein the computer is furtherconfigured to: determine a total number of tasks within the sequence oftasks and a total number of tasks for each of the one or more itemsbased on the accessed demand data of the one or more items.
 3. Thesystem of claim 2, wherein the one or more time intervals is determinedby calculating the ratio of the total number of tasks within thesequence of tasks and the total number of tasks for each of the one ormore items.
 4. The system of claim 1, wherein the computer is furtherconfigured to: determine a number of subsequences of tasks within thesequence of tasks for each of the one or more items which have at least[T_(A)] tasks, where [T_(A)] is the largest whole number smaller than orequal to the time interval of the item.
 5. The system of claim 4,wherein the computer is further configured to: for each of thesubsequence of tasks within the sequence of tasks calculate a weight ofeach of the one or more items based on:1+[|T _(A) −X|] wherein T_(A) is representative of the time interval foreach of the one or more items and X is representative of the number oftasks within the subsequence of tasks.
 6. The system of claim 5, whereinthe computer is further configured to: calculate a weighted average foreach of the one or more items in accordance with the determined numberof tasks within the subsequence of tasks and the calculated weight ofeach of the one or more items.
 7. The system of claim 1, wherein thecomputer is further configured to determine a new order of tasks withinthe sequence of tasks.
 8. A computer-implemented method of providinglevelness of a production schedule, comprising: accessing, by acomputer, demand data of one or more items to be processed within asequence of tasks; calculating, by the computer, one or more timeintervals for each of the one or more items; calculating, by thecomputer, a weighted average for each of the one or more items;calculating, by the computer, a time ratio according to the sequence oftasks by: calculating the average of the calculated time intervals andthe calculated weighted averages; and calculating a minimum ratio of anadjusted time interval for each of the one or more items and thecalculated weighted averages, upper bounded by unity; generating, by thecomputer, a production schedule based on a sequence of tasks having apredetermined calculated time ratio; and storing, by the computer, thegenerated production schedule in the database.
 9. The method of claim 8,further comprising: determining a total number of tasks within thesequence of tasks and a total number of tasks for each of the one ormore items based on the accessed demand data of the one or more items.10. The method of claim 9, wherein the one or more time intervals isdetermined by calculating the ratio of the total number of tasks withinthe sequence of tasks and the total number of tasks for each of the oneor more items.
 11. The method of claim 8, further comprising:determining a number of subsequences of tasks within the sequence oftasks for each of the one or more items which have at least [T_(A)]tasks, where [T_(A)] is the largest whole number smaller than or equalto the time interval of the item.
 12. The method of claim 11, furthercomprising: for each of the subsequences of tasks within the sequence oftasks calculating a weight of each of the one or more items based on:1+[|T _(A) −X|] wherein T_(A) is representative of the time interval foreach of the one or more items and X is representative of the number oftasks within the subsequence of tasks.
 13. The method of claim 12,further comprising: calculating a weighted average for each of the oneor more items in accordance with the determined number of tasks withinthe subsequence of tasks and the calculated weight of each of the one ormore items.
 14. The method of claim 8, further comprising: determining anew order of tasks within the sequence of tasks.
 15. A non-transitorycomputer-readable medium embodied with software providing levelness of aproduction schedule, the software when executed using one or morecomputers is configured to: access demand data of one or more items tobe processed within a sequence of tasks; calculate one or more timeintervals for each of the one or more items; calculate a weightedaverage for each of the one or more items; calculate a time ratioaccording to the sequence of tasks by: calculating the average of thecalculated time intervals and the calculated weighted averages; andcalculating a minimum ratio of an adjusted time interval for each of theone or more items and the calculated weighted averages, upper bounded byunity; generate a production schedule based on a sequence of taskshaving a predetermined calculated time ratio; and store the generatedproduction schedule in the database.
 16. The non-transitorycomputer-readable medium of claim 15, wherein the software is furtherconfigured to: determine a total number of tasks within the sequence oftasks and a total number of tasks for each of the one or more itemsbased on the accessed demand data of the one or more items.
 17. Thenon-transitory computer-readable medium of claim 16, wherein the one ormore time intervals is determined by calculating the ratio of the totalnumber of tasks within the sequence of tasks and the total number oftasks for each of the one or more items.
 18. The non-transitorycomputer-readable medium of claim 15, wherein the software is furtherconfigured to: determine a number of subsequences of tasks within thesequence of tasks for each of the one or more items which have at least[T_(A)] tasks, where [T_(A)] is the largest whole number smaller than orequal to the time interval of the item.
 19. The non-transitorycomputer-readable medium of claim 18, wherein the software is furtherconfigured to: for each of the subsequence of tasks within the sequenceof tasks calculate a weight of each of the one or more items based on:1+[|T _(A) −X|] wherein T_(A) is representative of the time interval foreach of the one or more items and X is representative of the number oftasks within the subsequence of tasks.
 20. The non-transitorycomputer-readable medium of claim 19, wherein the software is furtherconfigured to: calculate a weighted average for each of the one or moreitems in accordance with the determined number of tasks within thesubsequence of tasks and the calculated weight of each of the one ormore items.